Traditional mobile communication system (MCS) radio network optimization is done by extensive and expensive manual work such as drive/walk tests. In this setup, test terminals inside a car or a bag (in the case of a walk test) are used to perform numerous calls (voice, video, internet download/upload, etc.) and the results are logged to be input for a human user for post-processing. Apart from being inefficient in terms of lead time and capital costs, drive test based optimization provides coarse tuning options which cannot solve most of the network problems due to its limited sampling both in terms of time and space.
Optimization decisions that are based on individual drive test call results lack multipoint or regional analyses. On the other hand, non-drive test based prior art methods generally consider performance metrics (counters, KPIs) of a specific RAT (e.g., E-UTRAN). In a multi-RAT wireless communication network, configuration changes in one RAT can affect the performance of underlying RAT(s). Thus, there is a need for an efficient method which considers wireless communication radio network as a whole to find optimum network configuration to satisfy most of the network problems without causing additional harm due to unexpected indirect influence on other parts of the network.